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Satellite Ocean Aerosol Retrieval (SOAR) Algorithm Extension to S-NPP VIIRS as Part of the 'Deep Blue' Aerosol Project

Authors :
Alexander Smirnov
Corey Bettenhausen
N. C. Hsu
Woogyung Kim
Andrew M. Sayer
Jaehwa Lee
Source :
Journal of Geophysical Research: Atmospheres. 123:380-400
Publication Year :
2018
Publisher :
American Geophysical Union (AGU), 2018.

Abstract

The Suomi National Polar-Orbiting Partnership (S-NPP) satellite, launched in late 2011, carries the Visible Infrared Imaging Radiometer Suite (VIIRS) and several other instruments. VIIRS has similar characteristics to prior satellite sensors used for aerosol optical depth (AOD) retrieval, allowing the continuation of space-based aerosol data records. The Deep Blue algorithm has previously been applied to retrieve AOD from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) measurements over land. The SeaWiFS Deep Blue dataset also included a SeaWiFS Ocean Aerosol Retrieval (SOAR) algorithm to cover water surfaces. As part of NASA's VIIRS data processing, Deep Blue is being applied to VIIRS data over land, and SOAR has been adapted from SeaWiFS to VIIRS for use over water surfaces. This study describes SOAR as applied in version 1 of NASA's VIIRS Deep Blue data product suite. Several advances have been made since the SeaWiFS application, as well as changes to make use of the broader spectral range of VIIRS. A preliminary validation against Maritime Aerosol Network (MAN) measurements suggests a typical uncertainty on retrieved 550 nanometers AOD of order plus or minus (0.03 plus 10 percent), comparable to existing SeaWiFS/MODIS aerosol data products. Retrieved Angstrom exponent and fine mode AOD fraction are also well-correlated with MAN data, with small biases and uncertainty similar to or better than SeaWiFS/MODIS products.

Details

ISSN :
2169897X
Volume :
123
Database :
OpenAIRE
Journal :
Journal of Geophysical Research: Atmospheres
Accession number :
edsair.doi...........5b9a184c8c866a374f607c66c0d622f0
Full Text :
https://doi.org/10.1002/2017jd027412